Unifying Neural-network Quantum States and Correlator Product States via Tensor Networks

Correlator product states (CPS) are a powerful and very broad class of states for quantum lattice systems whose amplitudes can be sampled exactly and efficiently. Neural-network quantum states (NQS) are inspired by the restricted Boltzmann model used in machine learning.  By employing the formalism of tensor networks Stephen Clark shows that NQS are a special form of CPS with novel properties.

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